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CLAP model enables audio abuse detection in low-resource Indic languages

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a method for detecting audio abuse in low-resource Indic languages by leveraging the CLAP model. This approach bypasses the need for accurate speech-to-text transcription, which is often unreliable for these languages. By using CLAP's existing audio representations with a lightweight classifier, the system achieves performance close to fully supervised methods, even with minimal labeled data per language. This demonstrates CLAP's potential as a cost-effective foundation for cross-lingual audio abuse detection. AI

IMPACT Lowers the barrier for audio abuse detection in under-resourced languages, potentially improving online safety.

RANK_REASON Research paper detailing a new method for audio abuse detection. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

CLAP model enables audio abuse detection in low-resource Indic languages

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Research paper detailing a new method for audio abuse detection. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Aditya Narayan Sankaran, Reza Farahbakhsh, Noel Crespi ·

    Few-Shot Contrastive Adaptation for Audio Abuse Detection in Low-Resource Indic Languages

    arXiv:2604.09094v2 Announce Type: replace-cross Abstract: Abusive and hateful speech is increasingly spoken rather than written, surfacing in voice notes, calls, and short-form videos. Most detection systems still transcribe speech to text before classifying it, but transcription…

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